Tech to lower workplace stress

New tools can help identify at-risk employees

By Bob Parks

People are frequently off base when reporting their own
emotional states

New emotion‑detection tools use machine
intelligence to detect and reduce stress

For over a decade, a team of MIT scientists has been testing special
stress‑tracking sensors on drivers in the Boston area. The
wrist‑mounted devices monitor perspiration levels and other physical
indicators of stress, then upload data after each commute.

One takeaway from multiple trials: People are frequently off base
when reporting their own emotional states. Researchers frequently
interviewed drivers about their biggest stressors in traffic, but
didn’t glean many specifics beyond the usual: merging onto on‑ramps or
getting stuck in gridlock.

Instead, drivers showed the most stress in response to situations
that cropped up out of nowhere—for example, when a mom and a baby
stroller crossed in front of one driver while cars from behind bore down.

The driving tests, led by Rosalind Picard, director of MIT’s
Affective Computing group, are actually a useful proxy for workplace
stress, a growing problem that is the subject of Picard’s current research.

Turns out people are equally bad at identifying and predicting
stress at the office. The health consequences are alarming: Workplace
stress is now the fifth‑leading cause of death in the U.S., according
to research by Jeffrey Pfeffer, professor at Stanford University’s
Graduate School of Business.

That’s one reason why academic researchers and a number of startups
are pairing an established technology called emotion recognition with
new forms of machine intelligence that can detect and reduce worker
stress in ways that not even the most empathetic managers could do on
their own.

Businesses have begun tapping Picard’s team and others to supply new
tools that can identify stress and other emotional states. The use
cases cover a wide spectrum, from managing customer service calls, to
improving productivity in teams with low morale, to helping
overextended employees maintain work‑life balance.

“A great way to find the inefficiencies in a business process,” says
Picard, “is to find out where people are most frustrated and stressed.”

Sentiment detectors

In the early 2010s, market researchers adopted the first wave of
emotion recognition tools. One common application was video analysis
of consumer expressions as they tried new products.

Other apps crunched through millions of tweets to evaluate consumer
sentiment about product launches. Today consumer sentiment analysis is
a multi‑billion‑dollar industry that should grow rapidly over the next
five years, according to market research firm Tractica.

Creep factor

To be sure, there’s a creep factor associated with
emotion‑recognition tools. Some workers may find them invasive or not
trust their employers to use the data responsibly. The practice could
easily become coercive if used for critical HR decisions on
individuals. Companies that jump into the field with less than
transparent motives could face lawsuits and walkouts.

Picard acknowledges these hurdles, but believes that third‑party
data banks could securely handle aggregated results for employers, and
offer employees their own data as feedback when requested. If
accomplished through trust and employee consent, such data could be
seen as a valuable professional development benefit. “These tools help
us get insight into the stressors that people don’t even themselves
consciously acknowledge,” says Picard.

Boston‑based software company Cogito has built an app based on
machine‑learning algorithms that listen in on customer‑service calls
for Humana, MetLife and others. The goal is to identify stress in
employee‑customer interactions. When agents grow frazzled after long
hours of explaining insurance policies to customers, an upbeat voice
tells the agent that her own stress is coming through on the call.

For the banking industry, U.K.‑based Behavox monitors account reps
for tone and speed to help managers track employee performance. And
emotion‑tech firm Affectiva recently announced AI tools for
ride‑sharing services that analyze driver facial expressions for signs
of stress and burnout.

Other companies are exploring new ways of understanding the subtle
mechanisms of employee performance. Humanyze, a emotion analytics
firm, asks employees to wear a small microphone‑fitted sensor that
captures voice data and analyzes the tone and frequency of worker
interactions throughout the day. (The system is strictly opt‑in, and
employees who don't wear the badge are given dummy look‑alikes.)

One client, a major U.S. bank, worked with Humanyze to solve a staff
morale problem. One call center location had higher turnover rates and
burnout levels than others, and bank managers couldn’t put their
finger on the cause.

Humanyze sensors and software determined that call centers where
employees took breaks together lowered stress and built cohesion. At
the underperforming branch, managers had enforced a policy of
staggered breaks, preventing service reps from socializing. A new
break policy helped turn things around: Within months, worker
productivity at the site rose 23%; employee retention rates increased 28%.

Turning off the rational brain

Researchers have always struggled to determine how subjects really
feel, says Jeremy Pincus, a psychologist who co‑invented a tool called
MindSight for marketing intelligence firm Isobar. Pincus designed the
device to distract test subjects into providing more accurate
emotional feedback.

The test flashes seemingly random, surprising images—a skydiver in
flight, car driving off a cliff, a butterfly trapped in a cage—while
asking employees to tap those images that represent how their jobs
make them feel.

Pincus has gathered evidence over the years that shows how the speed
of the images forces subjects to blurt out their true feelings without
thinking. When volunteer employees at a major CPG company recently
took the MindSight survey to comment on the company’s new mission
statement, managers were surprised by the results.

“The statement said management wanted to give employees more
ownership over their jobs,” says Pincus. “But this cuts both ways: It
pushed workers toward higher achievement, but also made them more
anxious. Subjects connected the added responsibilities associated with
self‑direction to operating all alone without a safety net.”

This is precisely the kind of workplace stress that MIT’s Picard
wants to detect and alleviate. Her latest venture, Empatica, makes a
wristwatch that tracks stress through the skin. It also serves as an
alert for people experiencing epileptic seizures. The devices have
been used to test emotional states in research subjects at NASA, Sony
and Microsoft.

If high levels of emotional intelligence are considered an important
differentiator of successful leaders, tools like Picard’s suggest that
a company’s collective EQ isn’t just measurable but could eventually
become an important benchmark of long‑term success.

Bob Parks is a freelance writer for Businessweek, Wired, and
other publications.